library(flexdashboard)
library(readr)
library(lubridate)
library(shiny)
library(jsonlite)
library(maptools)
library(ggplot2)
library(tidyr)
library(dplyr)
library(purrr)
library(leaflet)
library(plotly)
library(DT)
library(ggthemes)
library(viridis)
library(tidyverse)
library(tigris)
nyc_squirrels <- read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-10-29/nyc_squirrels.csv")
nyc_squirrels_clean <- nyc_squirrels %>%
select(long, lat, unique_squirrel_id, hectare, date, hectare_squirrel_number,
age, primary_fur_color, highlight_fur_color, running, chasing,
climbing, eating, foraging, kuks, quaas, moans, tail_flags,
tail_twitches, indifferent, runs_from, community_districts,
police_precincts) %>%
mutate(date = mdy(date)) %>%
na.omit()central_park <- metro_divisions(class = "sf") %>%
filter(NAME == "New York-Jersey City-White Plains, NY-NJ")
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|======================================================================| 100%# leaflet map for central park
leaflet() %>%
addTiles() %>%
fitBounds(-73.9823592,40.7636484,-73.9492441, 40.800553)## Table 1
primary_fur_color <- nyc_squirrels_clean %>%
group_by(primary_fur_color) %>%
summarize(count = n())
df <- nyc_squirrels_clean %>%
group_by(running) %>%
summarize(count = n())